Leveraging Machine Learning Tools and Techniques for the Pre-Emptive Detection, Classification and Diagnosis of Bone-Fractures

Technologies that are developing quickly are constantly emerging in several fields, particularly the medical one. However, certain old-fashioned techniques are still frequently employed and productive. This is one of these approaches. X-rays are used to spot broken bones. The number of fractures can, however, occasionally be negligible and obscure. Systems that are effective and intelligent should be developed. In this investigation, a synthetic categorization system is being developed to classify bone fractures. The system that has been created consists of two main steps. The images of In the first stage, the fractures are processed using several image processing algorithms to determine their location and forms. The back propagation neural network is trained on the processed images before being used in the classification step, which comes next. The experiment tested the method on various images of bone fractures, and the results show high performance and a rate of categorization.